Do General Practitioners’ antibiotic prescribing decisions follow the STARWAVe clinical prediction rule?

Talk Code: 
U.17
Presenter: 
Martine Nurek
Twitter: 
Co-authors: 
Brendan Delaney, Olga Kostopoulou
Author institutions: 
Imperial College London

Problem

When children present with cough in primary care, prognostic uncertainty can lead to defensive antibiotic prescribing (“treat, just in case”). To combat this, a clinical prediction rule called “STARWAVe” was developed and validated. STARWAVe uses seven clinical factors (Short illness duration, Temperature, Age, Recession, Wheeze, Asthma, Vomiting) to estimate a child’s risk of deterioration (“very low” if ≤1 factor is present, “normal” if 2-3 are present, “high” if ≥4 are present). In so doing, it aims to reduce prognostic uncertainty and unnecessary prescribing in non-high risk cases. Providing STARWAVe as a decision aid to General Practitioners (GPs) could improve risk assessment and prescribing decisions. However, a risk score is merely a probability and could be ignored, especially if it contradicts the decision maker's intuitive assessment of risk. We aimed to compare GPs’ intuitive risk assessments and prescribing decisions to those of STARWAVe.

Approach

252 UK GPs were randomly assigned to view four (out of a possible eight) clinical vignettes online. Each vignette depicted a child presenting with cough, who was described in terms of the seven STARWAVe factors. Sytematically, we varied patient age (20 months vs. 5 years), illness duration (3 vs. 6 days), and the presence (vs. absence) of vomiting and wheeze, holding the remaining STARWAVe factors constant. Per vignette, GPs selected between “very low (e.g. 1 in 300)”, “medium (e.g. 1 in 70)” and “high (e.g. 1 in 8)” risk of deterioration. GPs also indicated whether they would prescribe antibiotics. We compared GPs’ risk classifications and prescribing decisions to those of STARWAVe, and assessed the influence of the manipulated factors using mixed-effects logistic regression.

Findings

GPs underestimated risk of deterioration in almost half of instances (46%, 459/1008) and overerestimated it in 9% (88/1008). Despite underestimating risk, they overprescribed: 78% of prescriptions were unnecessary relative to GPs’ own risk classification (121/156), and 83% relative to STARWAVe’s risk classification (130/156). In accordance with STARWAVe, GPs classified risk as higher for patients of 20 months vs. 5 years (OR=1.49 [1.14-1.95], p=0.003), though this did not influence prescribing (OR=0.92 [0.69-1.23], p=0.569). In contrast to STARWAVe, a shorter illness duration (3 vs. 6 days) decreased both risk classification (OR=0.54 [0.42-0.69], p<0.001) and prescribing odds (OR=0.34 [0.24-0.49], p<0.001). Vomiting and wheeze increased both risk classification and prescribing odds, in accordance with STARWAVe (OR_vomiting_risk=1.92 [1.57-2.36], OR_vomiting_prescribe=1.49 [1.24-1.80], OR_wheeze_risk=3.33 [2.66-4.16], OR_wheeze_prescribe=3.89 [2.66-5.69], all ps<0.001).

Consequences

Relative to the STARWAVe rule, GPs underestimated risk of deterioration. This was mainly because they assigned lower risk to a short (vs. long) illness duration. Still, they overprescribed, which suggests that risk classifications (as measured in this study) and prescribing decisions were not well-linked. Providing STARWAVe as a decision aid necessitates that GPs are aware of and agree with its assessment of clinical factors.

Submitted by: 
Martine Nurek
Funding acknowledgement: 
This work was supported by the National Institute for Health Research (NIHR) Patient Safety Translational Research Centre. The views expressed are those of the authors and not necessarily those of the NIHR or the Department of Health and Social Care.